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WorldForge V2: Eliciting Camera-Trajectory Alignment in Video Diffusion Models
Video diffusion models have learned rich 3D/4D priors, making them promising for scene generation and video re-rendering. However, their use in spatial tasks is limited by imprecise camera control, spatial and temporal inconsistencies, and entangled camera motion with scene dynamics. Existing approaches, such as task-specific fine-tuning and post-process warping, often introduce visual artifacts, generalize poorly, or incur high computational costs. We propose WorldForge V2 to achieve accurate camera control while preserving the generative capabilities of pretrained video models. We first deve
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- arXiv · AI, language, vision and robotics · 2026-10-22T17:53:03.000Z
First collected: 2026-10-23T07:12:42.771Z. This is not the publication date.